arXiv

MaRS: Robust Out-of-Distribution Detection via Mahalanobis Residual Scoring (opens in new tab)

Foundation models provide highly descriptive representations for medical images, yet their reliability degrades under distribution shifts arising from changes in patients, devices, or acquisition conditions. Reliable out-of-distribution (OOD) detection is therefore essential for safe deployment. Recent post-hoc detectors efficiently exploit frozen embeddings (\emph{e.g.}, kNN), whereas reconstruction-based OOD detection in latent feature space...

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